Adaptive clock throttling for event processing

ABSTRACT

Methods, apparatuses, and computer program products for adaptive clock throttling for event processing are provided. Embodiments include an event processing system receiving a plurality of events from one or more components of the distributed processing system. Embodiments also include the event processing system determining that an arrival attribute of the plurality of events exceeds an arrival threshold. Embodiments also include the event processing system, adjusting, in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, a clock speed of at least one of the event processing system and a component of the distributed processing system.

BACKGROUND OF THE INVENTION

Field of the Invention

The field of the invention is data processing, or, more specifically,methods, apparatuses, and computer program products for adaptive clockthrottling for event processing in a distributed processing system.

Description of Related Art

The development of the EDVAC computer system of 1948 is often cited asthe beginning of the computer era. Since that time, computer systemshave evolved into extremely complicated devices. Today's computers aremuch more sophisticated than early systems such as the EDVAC. Computersystems typically include a combination of hardware and softwarecomponents, application programs, operating systems, processors, buses,memory, input/output devices, and so on. As advances in semiconductorprocessing and computer architecture push the performance of thecomputer higher and higher, more sophisticated computer software hasevolved to take advantage of the higher performance of the hardware,resulting in computer systems today that are much more powerful thanjust a few years ago.

Modern distributed processing systems for intensive computing may havemillions of devices with many processes running on each device all ofwhich are capable of error and status reporting for automated errorrecovery, reporting to a systems administrator, and for other reasons.In many cases, in the case of an error for example, the sheer number ofsuch error reports and status reports are so overwhelming that theycannot be handled in a meaningful manner. For example, a systemsadministrator receiving a hundred thousand error reports may beoverwhelmed by the sheer number of such reports and therefore in theaggregate those reports become more and more unhelpful and irrelevant.

SUMMARY OF THE INVENTION

Methods, apparatuses, and computer program products for adaptive clockthrottling for event processing are provided. Embodiments include anevent processing system receiving a plurality of events from one or morecomponents of the distributed processing system. Embodiments alsoinclude the event processing system determining that an arrivalattribute of the plurality of events exceeds an arrival threshold.Embodiments also include the event processing system, adjusting, inresponse to determining that the arrival attribute of the plurality ofevents exceeds the arrival threshold, a clock speed of at least one ofthe event processing system and a component of the distributedprocessing system.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescriptions of exemplary embodiments of the invention as illustrated inthe accompanying drawings wherein like reference numbers generallyrepresent like parts of exemplary embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary system for adaptive clock throttling forevent processing in a distributed processing system according toembodiments of the present invention.

FIG. 2 sets forth a block diagram of automated computing machinerycomprising an exemplary computer useful in adaptive clock throttling forevent processing in a distributed processing system according toembodiments of the present invention.

FIG. 3 sets forth a block diagram of an exemplary system for adaptiveclock throttling for event processing in a distributed processing systemin a distributed processing system according to embodiments of thepresent invention.

FIG. 4 sets forth a diagram illustrating assigning events to an eventspool according to embodiments of the present invention.

FIG. 5 sets forth a diagram illustrating assigning alerts to an alertspool according to embodiments of the present invention.

FIG. 6 sets forth a flow chart illustrating an example method ofadaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention.

FIG. 7 sets forth a flow chart illustrating an additional method ofadaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention.

FIG. 8 sets forth a flow chart illustrating an additional method ofadaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention.

FIG. 9 sets forth a flow chart illustrating an additional method ofadaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention.

FIG. 10 sets forth a flow chart illustrating an additional method ofadaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Exemplary methods, apparatuses, and computer program products foradaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention aredescribed with reference to the accompanying drawings, beginning withFIG. 1. FIG. 1 illustrates an exemplary system for adaptive clockthrottling for event processing in a distributed processing system (101)according to embodiments of the present invention. A distributedprocessing system is typically implemented as multiple autonomous orsemi-autonomous computers that communicate through a computer network.In such example distributed processing systems, the computers ofteninteract with each other in order to achieve a common goal. A computerprogram that runs in such an example distributed system is typicallycalled a distributed program, and distributed programming is often usedto describe the process of writing such programs.

In the example of FIG. 1, the distributed processing system (101) isimplemented as a parallel computer (100), non-volatile memory for thecomputer in the form of data storage device (118), an output device forthe computer in the form of a printer (120), and an input/output devicefor the computer in the form of a computer terminal (122). The parallelcomputer (100) in the example of FIG. 1 includes a plurality of computenodes (102). Each compute node (102) is an automated computing devicecomposed of one or more computer processors, its own computer memory,and its own input/output functionality. The compute nodes (102) arecoupled for data communications by several independent datacommunications networks including a high speed Ethernet network (174), aJoint Test Action Group (‘JTAG’) network (104), a collective or treenetwork (106) which is optimized for collective operations, and a torusnetwork (108) which is optimized for point to point operations. The treenetwork (106) is a data communications network that includes datacommunications links connected to the compute nodes (102) so as toorganize the compute nodes (102) as a tree. Each data communicationsnetwork is implemented with data communications links among the computenodes (102). The data communications links provide data communicationsfor parallel operations among the compute nodes of the parallel computer(100).

In addition to the compute nodes (102), the parallel computer (100)includes input/output (‘I/O’) nodes (110, 114) coupled to the computenodes (102) through the high speed Ethernet network (174). The I/O nodes(110, 114) provide I/O services between the compute nodes (102) and I/Odevices, which in this example is the data storage device (118), theprinter (120) and the terminal (122). The I/O nodes (110, 114) areconnected for data communications through a local area network (‘LAN’)(130). The parallel computer (100) also includes a service node (116)coupled to the compute nodes (102) through the JTAG network (104). Theservice node (116) provides service common to the compute nodes (102),such as loading programs into the compute nodes (102), starting programexecution on the compute nodes (102), retrieving results of programoperations on the compute nodes (102), and so on. The service node (116)runs an event and alert analysis module (124) and communicates with asystem administrator (128) through a service application interface (126)that runs on the computer terminal (122).

Many of the components of the distributed processing system of FIG. 1,that is the devices of the distributed processing system or processesrunning on the devices of the distributed processing system of FIG. 1,are capable of some form of error or status reporting through events andmany of such components are also capable of receiving alerts in responseto one or more of such events. Often in distributed processing systemshundreds of thousands or millions of components may provide or receiveincidents, often in the form of events or alerts.

An incident is a generic term used in this specification to mean anidentification or notification of a particular occurrence on a componentof a distributed processing system such as events described below, arefined identification of an occurrence often based on events such as analert described below, or other notifications as will occur to those ofskill in the art.

Incidents are administered in pools for event and alert analysisaccording to embodiments of the present invention. A pool of incidentsis a collection of incidents organized by the time of either theiroccurrence, by the time they are logged in an incident queue, includedin the pool, or other time as will occur to those of skill in the art.Such incident pools often provide the ability to analyze a group of timerelated incidents. Often such incident pools are useful in identifyingfewer and more relevant incidents in dependence upon multiple relatedincidents.

An event according to embodiments of the present invention is anotification of a particular occurrence in or on a component of thedistributed processing system. Such events are sent from the componentupon which the occurrence occurred or another reporting component to anevent and alert analysis module according to the present invention.Often events are notifications of errors occurring in a component of thedata processing system. Events are often implemented as messages eithersent through a data communications network or shared memory. Typicalevents for event and alert analysis according to embodiments of thepresent invention include attributes such as an occurred time, a loggedtime, an event type, an event ID, a reporting component, and a sourcecomponent, and other attributes.

An alert according to embodiments of the present invention is a refinedidentification of an occurrence, such as an error, based upon more thanone event and therefore provides an identification of the occurrence inthe context of its operation in the distributed processing system. Oftenan alert may be a notification of a particular error type of occurrencethat is identified in dependence upon the plurality of events receivedfrom one or more components of the data processing system, such as, forexample, a link failure among a plurality of devices each of which areproducing many events based upon the single link failure, or a powerfailure provoking thousands of events, and so on.

Alerts are often implemented as messages to be sent through a datacommunications network or shared memory. Typical alerts according toembodiments of the present invention have attributes attached to thembased upon the attributes of the events received from which they areidentified.

The event and alert analysis module (124) includes at least two incidentanalyzers implemented as an event analyzer and an alert analyzer capableof adaptive clock throttling for event processing in a distributedprocessing system according to embodiments of the present invention. Theevent and alert analysis module (124) is also implemented as a monitorand checkpoint manager for managing the checkpoints from the incidentanalyzers.

Specifically, the event and alert analysis module (124) is implementedas automated computing machinery configured to receive a plurality ofevents from one or more components of the distributed processing systemand determine that an arrival attribute of the plurality of eventsexceeds an arrival threshold. The event and alert analysis module isalso configured to adjust, in response to determining that the arrivalattribute of the plurality of events exceeds the arrival threshold, aclock speed of at least one of the event and alert analysis module and acomponent of the distributed processing system.

The arrangement of nodes, networks, and I/O devices making up theexemplary distributed processing system illustrated in FIG. 1 are forexplanation only, not for limitation of the present invention.Distributed data processing systems configured to perform adaptive clockthrottling for event processing according to embodiments of the presentinvention may include additional nodes, networks, devices, andarchitectures, not shown in FIG. 1, as will occur to those of skill inthe art. The parallel computer (100) in the example of FIG. 1 includessixteen compute nodes (102). Parallel computers configured to performadaptive clock throttling for event processing according to embodimentsof the present invention sometimes include thousands of compute nodes.In addition to Ethernet, JTAG, collective, and point to point, networksin such data processing systems may support many data communicationsprotocols including for example TCP (Transmission Control Protocol), IP(Internet Protocol), and others as will occur to those of skill in theart. Various embodiments of the present invention may be implemented ona variety of hardware platforms in addition to those illustrated in FIG.1.

Adaptive clock throttling for event processing in a distributedprocessing system in accordance with the present invention is generallyimplemented with computers, that is, with automated computing machinery.In the system of FIG. 1, for example, all the service nodes, I/O nodes,compute nodes, of the parallel computer are implemented to some extentat least as computers. For further explanation, therefore, FIG. 2 setsforth a block diagram of automated computing machinery comprising anexemplary computer (252) useful in performing adaptive clock throttlingfor event processing according to embodiments of the present invention.The computer (252) of FIG. 2 includes at least one computer processor(256) or ‘CPU’ as well as random access memory (268) (‘RAM’) which isconnected through a high speed memory bus (266) and bus adapter (258) toprocessor (256) and to other components of the computer (252) andthrough an expansion bus to adapters for communications with othercomponents of a distributed processing system (101).

Stored in RAM (268) is an event and alert analysis module (124), amodule of automated computing machinery for performing adaptive clockthrottling for event processing according to embodiments of the presentinvention. The event and alert analysis module (124) includes twoincident analyzers, a monitor (204), and a checkpoint manager (299)according to embodiments of the present invention.

The checkpoint manager (299) performs adaptive clock throttling forevent processing according to embodiments of the present invention byprocessing checkpoints from the incident analyzers. The monitor (204) isconfigured to perform adaptive clock throttling for event processing ina distributed processing system according to embodiments of the presentinvention. In the example of FIG. 2, the monitor (204) receives eventsfrom components of the distributed processing system and puts thereceived events in an event queue. The monitor (204) of FIG. 2 mayreceive events from components of the distributed processing system ontheir motion, may periodically poll one or more of the components of thedistributed processing system, or receive events from components inother ways as will occur to those of skill in the art.

The incident analyzers include an event analyzer (208) and an alertanalyzer (218). The event analyzer of FIG. 2 is a module of automatedcomputing machinery capable of identifying alerts in dependence uponreceived events. That is, event analyzers typically receive events andproduce alerts. In many embodiments, event analyzers are implemented inparallel. Often such event analyzers are assigned to a particular poolof events and may be focused on events from a particular component orcaused by a particular occurrence to produce a more concise set ofalerts.

The alert analyzer (218) of FIG. 2 is a module of automated computingmachinery capable of identifying alerts for transmission from events andother alerts, identifying additional alerts for transmission, andsuppressing unnecessary, irrelevant, or otherwise unwanted alertsidentified by the event analyzer. That is, alert analyzers typicallyreceive alerts and events and produce or forward alerts in dependenceupon those alerts and events. In many embodiments, alert analyzers areimplemented in parallel. Often such alert analyzers are assigned to aparticular pool of alerts and may be focused on alerts with particularattributes to produce a more concise set of alerts.

In addition to the general functions described above, the event andalert analysis module (124) may be configured to perform adaptive clockthrottling for event processing in a distributed processing systemaccording to embodiments of the present invention. Specifically, theevent and alert analysis module (124) is implemented as automatedcomputing machinery configured to receive a plurality of events from oneor more components of the distributed processing system and determinethat an arrival attribute of the plurality of events exceeds an arrivalthreshold. The event and alert analysis module is also configured toadjust, in response to determining that the arrival attribute of theplurality of events exceeds the arrival threshold, a clock speed of atleast one of the event and alert analysis module and a component of thedistributed processing system.

Also stored in RAM (268) is an operating system (254). Operating systemsuseful for relevant alert delivery according to embodiments of thepresent invention include UNIX™, Linux™, Microsoft XP™, AIX™, IBM'si5/OS™, and others as will occur to those of skill in the art. Theoperating system (254), event and alert analysis module (124), the eventanalyzer (208), the alert analyzer (218) in the example of FIG. 2 areshown in RAM (268), but many components of such software typically arestored in non-volatile memory also, such as, for example, on a diskdrive (270).

The computer (252) of FIG. 2 includes disk drive adapter (272) coupledthrough expansion bus (260) and bus adapter (258) to processor (256) andother components of the computer (252). The disk drive adapter (272)connects non-volatile data storage to the computer (252) in the form ofdisk drive (270). Disk drive adapters useful in computers for adaptiveclock throttling for event processing according to embodiments of thepresent invention include Integrated Drive Electronics (‘IDE’) adapters,Small Computer System Interface (‘SCSI’) adapters, and others as willoccur to those of skill in the art. Non-volatile computer memory alsomay be implemented for as an optical disk drive, electrically erasableprogrammable read-only memory (so-called ‘EEPROM’ or ‘Flash’ memory),RAM drives, and so on, as will occur to those of skill in the art.

The example computer (252) of FIG. 2 includes one or more input/output(‘I/O’) adapters (278). I/O adapters implement user-orientedinput/output through, for example, software drivers and computerhardware for controlling output to display devices such as computerdisplay screens, as well as user input from user input devices (281)such as keyboards and mice. The example computer (252) of FIG. 2includes a video adapter (209), which is an example of an I/O adapterspecially designed for graphic output to a display device (280) such asa display screen or computer monitor. The video adapter (209) isconnected to processor (256) through a high speed video bus (264), busadapter (258), and the front side bus (262), which is also a high speedbus.

The exemplary computer (252) of FIG. 2 includes a communications adapter(267) for data communications with other computers (282) and for datacommunications with a data communications network (200). Such datacommunications may be carried out serially through RS-232 connections,through external buses such as a Universal Serial Bus (‘USB’), throughdata communications, data communications networks such as IP datacommunications networks, and in other ways as will occur to those ofskill in the art. Communications adapters implement the hardware levelof data communications through which one computer sends datacommunications to another computer, directly or through a datacommunications network. Examples of communications adapters useful foradaptive clock throttling for event processing according to embodimentsof the present invention include modems for wired dial-upcommunications, Ethernet (IEEE 802.3) adapters for wired datacommunications network communications, and 802.11 adapters for wirelessdata communications network communications.

For further explanation, FIG. 3 sets forth a block diagram of anexemplary system for adaptive clock throttling for event processing andrelevant alert delivery in a distributed processing system (102)according to embodiments of the present invention. The system of FIG. 3includes an event and alert analysis module (124). The event and alertanalysis module (124) of FIG. 3 receives in an event queue (306) aplurality of events (302) from one or more components of a distributedprocessing system (102). A component of a distributed processing systemaccording to embodiments of the present invention may be a device of thedistributed processing system or a process running on a device of thedistributed processing. Such components are often capable of some formof event transmission, often for error or status reporting.

An event according to embodiments of the present invention is anotification of a particular occurrence in or on a component of thedistributed processing system. Such events are sent from the componentupon which the occurrence occurred or another reporting component to anevent and alert analysis module according to the present invention.Often events are notifications of errors occurring in a component of thedata processing system. Events are often implemented as messages eithersent through a data communications network or shared memory. Typicalevents for event and alert analysis according to embodiments of thepresent invention include attributes such as an occurred time, a loggedtime, an event type, an event ID, a reporting component, and a sourcecomponent, and other attributes. An occurred time is the time at whichthe event occurred on the component. A logged time is the time the eventwas included in the event queue (306) and is typically inserted into theevent by a monitor. An event type is a generic type of event such as forexample, power error, link failure error, errors related to notreceiving messages or dropping packets and so on as will occur to thoseof skill in the art. An event ID is a unique identification of theevent. A reporting component is an identification of the component thatreported the event. A source component is an identification of thecomponent upon which the event occurred. In many cases, but not all, thereporting component and source component are the same component of thedistributed processing system.

The event and analysis module (124) of FIG. 3 also includes a checkpointmanager (299) that is configured to perform adaptive clock throttlingfor event processing in a distributed processing system according toembodiments of the present invention.

In the example of FIG. 3, the monitor (204) receives events fromcomponents of the distributed processing system and puts the receivedevents (302) in the event queue (306). The monitor (204) of FIG. 3 mayreceive events from components of the distributed processing system ontheir motion, may periodically poll one or more of the components of thedistributed processing system, or receive events from components inother ways as will occur to those of skill in the art.

The system of FIG. 3 also includes an event analyzer (208). The eventanalyzer (208) of FIG. 3 is a module of automated computing machineryconfigured to identify alerts in dependence upon received events. Thatis, event analyzers typically receive events and produce alerts. In manyembodiments, multiple event analyzers are implemented in parallel. Oftenevent analyzers are assigned to a particular pool of events and may befocused on events from a particular component or caused by a particularoccurrence to produce a more concise set of alerts.

As mentioned above, in some embodiments of the present invention, morethan one event analyzer may operate in parallel. As such, each eventanalyzer may maintain one or more events pools for performing adaptiveclock throttling for event processing according to embodiments of thepresent invention. Assigning by the event analyzer the events to anevents pool may therefore include selecting only events from one or moreparticular components. In such embodiments, particular components may beselected for a particular events pool to provide events associated witha particular period of time from a particular set of one or morecomponents.

Assigning by the event analyzer the events to an events pool may also becarried out by selecting only events of a particular event type. In suchembodiments, particular events may be selected for a particular eventspool to provide events associated with a particular period of time froma particular set of event types. The event analyzer (208) in the exampleof FIG. 3 identifies in dependence upon the event analysis rules (310)and the events assigned to the events pool, one or more alerts (314).

Event analyses rules (310) are a collection of predetermined rules formeaningfully parsing received events to identify relevant alerts independence upon the events.

The event analysis rules (310) of FIG. 3 include event arrival rules(330), events pool operation rules (332), event suppression rules (334),and events pool closure rules (336). The event arrival rules (330) areconfigurable predetermined rules for identifying alerts in dependenceupon events in real time as those events are assigned to the eventspool. That is, the event arrival rules (330) identify alerts independence upon events before closing the events pool. Such rules aretypically predetermined to identify particular alerts in dependence uponattributes of those events. Event arrival rules may for example dictateidentifying a particular predetermined alert for transmission to asystems administrator in dependence upon a particular event type orcomponent type for the event or other attribute of that event. Suchrules are flexible and may be tailored to a particular distributedcomputing system and its functions.

An alert according to embodiments of the present invention is a refinedidentification of an occurrence, such as an error based upon more thanone event, and therefore provides an identification of the occurrence inthe context of its operation in the distributed processing system. Oftenan alert may be a notification of a particular error type of occurrencethat is identified in dependence upon the plurality of events receivedfrom one or more components of the data processing system, such as, forexample, a link failure among a plurality of devices each of which areproducing many events based upon the single link failure, or a powerfailure provoking thousands of events, and so on.

Alerts are often implemented as messages to be sent through a datacommunications network or shared memory. Typical alerts according toembodiments of the present invention have attributes attached to thembased upon the attributes of the events received from which they areidentified.

The events pool operation rules (332) are configurable predeterminedrules for controlling the operations of the events pool. Such rulesincludes rules identifying the initial predetermined period of time foreach events pool, rules dictating the length of time extended to thepool upon the assignment of each new event to the pool, rules dictatingthe minimum time an event must be in a pool before that event isincluded in a collection of events when the pool is closed, rulesdictating the amount to extend the initial predetermined period of timebased on an arrival rate of events assigned to an events pool, rulesgoverning the closing of an events pool, and others as will occur tothose of skill in the art. Such rules are flexible and may be tailoredto a particular distributed computing system and its functions.

The event suppression rules (334) are configurable predetermined rulesfor suppressing one or more events in a closed pool of events used inidentifying alerts. That is, often events in the closed events pool maybe duplicate events, redundant events, or otherwise unnecessary orunhelpful events in identifying alerts. Such suppression rules aretypically predetermined to delete, drop, or otherwise ignore thosesuppressed events. Event suppression rules may for example dictate thatmore than a threshold number of events of a particular event type orcomponent type are to be suppressed. Such rules are also flexible andmay be tailored to a particular distributed computing system and itsfunctions.

The events pool closure rules (336) are configurable predetermined rulesfor identifying alerts in dependence upon unsuppressed events in theclosed events pool and alerts identified by the event arrival rules.That is, events pool closure rules identify new alerts in dependenceupon one or more or even all of the unsuppressed events in the closedevents pool. The events pool closure rules also identify alerts independence upon the alerts identified by the event arrival rules (330)or a combination of the alerts identified by the event arrival rules(330) and one or more of the unsuppressed events in the closed eventspool.

The event analyzer (208) in the example of FIG. 3 sends all the alerts(314) identified by the event analyzer (208) to an alert analyzer (218).The alert analyzer of FIG. 3 is a module of automated computingmachinery capable of identifying alerts for transmission from events andother alerts, identifying additional alerts for transmission, andsuppressing unnecessary, irrelevant, or otherwise unwanted or unhelpfulalerts identified by the event analyzer. That is, alert analyzerstypically receive alerts and events and produce or forward alerts independence upon those alerts and events. In many embodiments, alertanalyzers are implemented in parallel. The alerts (316) in the exampleof FIG. 3 are sent from the event analyzer (208) to the alert analyzer(218) through an alerts queue (316).

The alert analyzer (218) of FIG. 3 assigns each of the identified alerts(314) to an alerts pool (324). An alerts pool is a collection of alertsorganized by the time of one or more the events causing the alert to beidentified, the time the alert is identified, or other time as willoccur to those of skill in the art. That is, alerts pools are acollection of alerts organized by time. Such alerts pools often providethe ability to analyze groups alerts identified and included in thealerts pool according to some time. Often such alerts pools are usefulin identifying fewer and more relevant alerts in dependence uponmultiple related events and multiple related alerts.

The alert analyzer (218) of FIG. 3 determines in dependence upon alertanalysis rules (322) and the alerts in the alerts pool whether tosuppress any alerts. Suppressing an alert is typically carried out bydropping the alert, deleting the alert or otherwise ignoring or nottransmitting the suppressed alert to a component of the distributedprocessing system.

The alert analysis rules (322) are a collection of rules for suppressingone or more alerts to provide a more relevant set of alerts fortransmission to a component of the distributed processing system, suchas for example, for display to a systems administrator and to identifyadditional alerts for transmission to one or more components of thedistributed processing system. Alert analysis rules for example maydictate that duplicate alerts are to be suppressed, alerts of aparticular type for transmission to a particular component are to besuppressed, alerts of a particular type be transmitted to a particularcomponent are to be suppressed and so on as will occur to those of skillin the art. Such alerts may be more meaningful to a component of thedistributed processing system for automated error recovery or for asystems administrator who may otherwise be less informed by a number ofraw unanalyzed alerts.

The alert analyzer (218) of FIG. 3 also has access to the events queue(306). The alert analyzer (218) of FIG. 3 in dependence upon the alertanalysis rules may, in some embodiments select events from the eventsqueue and determine whether to suppress any alerts in dependence uponthe selected events. That is, alert analysis rules may also take intoaccount events and their attributes for suppressing alerts and foridentifying additional alerts for transmission to one or morecomponents. Such events may be related to the alerts in the alerts poolor independent from such alerts.

The alert analyzer (218) of FIG. 3 transmits the unsuppressed alerts toone or more components of the distributed processing system. The alertanalyzer may transmit the unsuppressed alerts to one or more componentsof the distributed processing system by sending the alert as a messageacross a data communications network, through shared memory, or in otherways as will occur to those of skill in the art. In the example of FIG.3, the unsuppressed alerts (320) are transmitted to the terminal (122)for display to the systems administrator (128).

The alert analyzer (218) of FIG. 3 is also configured to identify independence upon alert analysis rules (322), the alerts in the alertspool (324), and selected events (306) one or more additional alerts andtransmitting the one or more components of the distributed processingsystem. The additional alerts may include one or more alerts notidentified by the event analyzer. Such additional alerts may provideadditional information to a component of the distributed processingsystem of a systems administrator.

In the system of FIG. 3, events (302) are received and analyzed by eventanalyzers (208) with event analysis rules (310). Based on the eventanalysis rules (310), the event analyzers (208) generate the alerts(314). These alerts may be sent to a delivery queue (399) for immediatedelivery to the system administrator (128) and the distributedprocessing system (102). These alerts may also be sent to alertanalyzers (218) for further processing and generation of additionalalerts (320), which may also be provided to the delivery queue (399).The event and alert analysis module (124) also includes an alertdatabase (397) for recording alerts that have generated by the event andalert analysis module (124).

The event and alert analysis module (124) is also configured to receivea plurality of events from one or more components of the distributedprocessing system and determine that an arrival attribute of theplurality of events exceeds an arrival threshold. The event and alertanalysis module is also configured to adjust, in response to determiningthat the arrival attribute of the plurality of events exceeds thearrival threshold, a clock speed of at least one of the event and alertanalysis module and a component of the distributed processing system.

As mentioned above, adaptive clock throttling for event processingaccording to embodiments of the present invention may include assigningevents to an events pool and those pools are administered according toembodiments of the present invention. For further explanation, FIG. 4sets forth a diagram illustrating assigning events to an events poolaccording to embodiments of the present invention. An events pool (312)is a collection of events organized by the time of either theiroccurrence, by the time they are logged in the event queue, included inthe events pool, or other time as will occur to those of skill in theart. That is, events pools are a collection of events organized by time.Such events pools often provide the ability to analyze a group of timerelated events and to identify alerts in dependence upon them. Oftensuch events pools are useful in identifying fewer and more relevantalerts in dependence upon multiple related events.

Events pools according to embodiments of the present invention aretypically operated according to events pool operation rules which arethemselves often included in event analysis rules. Such events pooloperation rules are configurable predetermined rules for controlling theoperations of the events pool. Such rules includes rules identifying theinitial predetermined period of time for each events pool, rulesdictating the length of time extended to the pool upon the assignment ofeach new event to the pool, rules dictating the minimum time an eventmust be in a pool before that event is included in a collection ofevents when the pool is closed, rules dictating the amount to extend theinitial predetermined period of time based on an arrival rate of eventsassigned to an events pool, rules governing the closing of an eventspool, and others as will occur to those of skill in the art. Such rulesare flexible and may be tailored to a particular distributed computingsystem and its functions.

Events are often assigned to an events pool according to their loggedtime. That is, events are typically inserted into the events pool in theorder that they are received in the event queue. In the example of FIG.4, the timing of the events pool (312) is initiated when the first event‘Event 0’ (400) is assigned to the events pool (312) at time t₀. Theevents pool of FIG. 4 is initiated for a predetermined initial period oftime from t₁ to t_(f). That is, upon receiving the first event ‘Event 0’(400) the events pool of FIG. 4 has a predetermined initial period oftime beginning at t₁ and ending at t_(f). The predetermined initialperiod of time may be configured in dependence upon a number of factorsas will occur to those of skill in the art such as, the number ofcomponents in the distributed processing system, the frequency ofreceiving events, the types of events typically received and so on aswill occur to those of skill in the art.

In the example FIG. 4, the initial period of time is extended for eachnew event assigned to the events pool during the predetermined initialperiod from t₁ to t_(f) by a particular period of time assigned to theevent. In the example of FIG. 4 upon assigning ‘Event 1’ (402) to theevents pool (312) the predetermined initial period of time t₀-t_(f) isextended by ‘Extension 1’ (406) having a time of e1 thereby creating anew time for closing the events pool (312) at t_(f+e1) if no otherevents are assigned to the pool before t_(f+e1). Similarly, in theexample of FIG. 4 upon assigning ‘Event 2’ (404) to the events poolhaving a time of e2, the now extended period of time from t₀-t_(f+e1) isextended again by extension 2 (406) thereby establishing a new time forclosing the pool at time t_(f−e1−e2) if no other events are assigned tothe pool before t_(f+e1+e2) or before some maximum time for the eventspool has expired. In this manner, the events pool is extended with eachreceived event until a collection of events that may be usefully used toidentify alerts is assigned to the events pool. According to embodimentsof the present invention, the predetermined initial period of time maybe extended based on an arrival rate at which events are assigned to anevents pool.

In typical embodiments of the present invention, events pools may have amaximum duration that can no longer be extended. In such cases, arequirement may exist that an event that has not resided in the eventspool for a threshold period of time be moved to a next events pool. Insome embodiments, the attributes of such an event that is moved to thenext events pool are used for relevant alert delivery with the initialevents pool and in other embodiments; the attributes of such an eventare used for relevant alert delivery with the next events pool to whichthat event is moved.

In the example of FIG. 4, when conditions are met to close the pool anevents analyzer determines for each event (400, 402, 404) in the eventspool (312) whether the event has been in the pool for its predeterminedminimum time for inclusion in a pool. If the event has been in the poolfor its predetermined minimum time, the event is included in the closedpool for event analysis for relevant alert delivery. If the event hasnot been in the pool for its predetermined minimum time, the event isevicted from the closed pool and included a next pool for event analysisfor relevant alert delivery.

In many embodiments, a plurality of events pools may be used in paralleland one or more of such events pools are assigned to a particular eventsanalyzer. In such embodiments, events analyzers may be directed toevents in events pools having particular attributes.

As mentioned above, adaptive clock throttling for event processingaccording to embodiments of the present invention may include assigningalerts to an alerts pool and those pools are administered according toembodiments of the present invention. For further explanation, FIG. 5sets forth a diagram illustrating assigning alerts to an alerts poolaccording to embodiments of the present invention. The alerts pool (324)of FIG. 5 operates in a manner similar to the events pool of FIG. 4.That is, the alerts pool according to the example of FIG. 5 includesalerts and the timing of the alerts pool begins with the first alert‘Alert 0’ (500) at time t₀ and is configured to have a predeterminedinitial period of time t₀-tf. In the example of FIG. 5, the initialperiod of time is extended for each new alert assigned to the alertspool in the predetermined initial period from t₁ to t_(f) by aparticular period of time assigned to the alert. In the example of FIG.5, upon assigning ‘Alert 1’ (502) to the alerts pool (324) thepredetermined initial period of time t₀-t_(f) is extended by ‘Extension1’ (506) having a time of e1 thereby creating a new time for closing thealerts pool (324) at t_(f+e1) if no other alerts are assigned to thepool before t_(f+e1). Similarly, in the example of FIG. 5 upon assigning‘Alert 2’ (504) to the alerts pool having a time of e2, the now extendedperiod of time from t₀-t_(f+e1) is extended again by ‘Extension 2’ (506)thereby establishing a new time for closing the pool at time t_(f+e1+e2)if no other alerts are assigned to the pool before t_(f+e1+e2) or beforesome maximum time for the alerts pool has expired. According toembodiments of the present invention, the predetermined initial periodof time may be extended based on an arrival rate at which alerts areassigned to an alerts pool.

In typical embodiments of the present invention, alerts pools may have amaximum duration that can no longer be extended. In such cases, arequirement may exist that an alert that has not resided in the alertspool for a threshold period of time be moved to a next alerts pool. Insome embodiments, the attributes of such an alert that is moved to thenext alerts pool are used for relevant alert delivery according toembodiments of the present invention with the initial alerts pool and inother embodiments, the attributes of such an alert are used for relevantalert delivery with the next alerts pool to which that alert is moved.

In the example of FIG. 5, when conditions are met to close the pool analerts analyzer determines for each alert (500, 502, 504) in the pool(324) whether the alert has been in the pool for its predeterminedminimum time for inclusion in a pool. If the alert has been in the poolfor its predetermined minimum time, the alert is included in the closedpool for alert analysis for relevant alert delivery according toembodiments of the present invention. If the alert has not been in thepool for its predetermined minimum time, the alert is evicted from theclosed pool and included a next pool for alert analysis for relevantalert delivery according to embodiments of the present invention.

In many embodiments, a plurality of alerts pools may be used in paralleland one or more of such alerts pools are assigned to a particular alertsanalyzer. In such embodiments, alerts analyzers may be directed toalerts in alerts pools having particular attributes.

As mentioned above, adaptive clock throttling for event processingaccording to embodiments of the present invention may include theadministration of one or more pools of incidents such as events, alertsor other incidents as will occur to those of skill in the art. Forfurther explanation, FIG. 6 sets forth a flow chart illustrating anexample method of performing adaptive clock throttling for eventprocessing for incident analysis in a distributed processing system in adistributed processing system according to embodiments of the presentinvention. The method of FIG. 6 includes receiving (602) in an eventqueue a plurality of events (302) from one or more components of adistributed processing system. Attributes of events useful in performingadaptive clock throttling for event processing for incident analysis ina distributed processing system according to embodiments of the presentinvention may include an occurred time, a logged time, an event type, anevent ID, a reporting component, and a source component.

Receiving (602) in an event queue a plurality of events (302) from oneor more components of a distributed processing system may be carried outby receiving an event initiated by one or more components of the dataprocessing system and storing the event in the event queue according tothe time in which the event occurred or according to the time the eventwas received. Receiving (602) in an event queue a plurality of events(302) from one or more components of a distributed processing systemalso may be carried out by polling a component for status and receivingin response an event and storing the event in the event queue accordingto the time in which the event occurred or according to the time theevent was received.

The method of FIG. 6 also includes assigning (604) by an event analyzereach received event to an events pool (312). In some embodiments of thepresent invention, assigning (604) by an event analyzer each receivedevent (302) to an events pool (312) may be carried out by assigningevents to the events pool according to the logged time. Assigning (604)by an event analyzer each received event (302) to an events pool (312)may also be carried out in dependence upon attributes of the event. Suchattributes may include an identification or type of the component uponwhich an occurrence occurred to create the event, the reportingcomponent of the event, the event ID, the event type, and so on as willoccur to those of skill in the art.

An events pool according to the method of FIG. 6 includes eventsoccurring during a predetermined initial period of time and in theexample of FIG. 6 assigning (604) by the event analyzer each receivedevent to an events pool includes extending (626) for each event assignedto the events pool the predetermined initial period of time by aparticular period of time assigned to the event.

The event analyzer includes event analysis rules (310) including, eventarrival rules, events pool operation rules, event suppression rules, andevents pool closure rules. Event arrival rules are configurablepredetermined rules for identifying alerts in dependence upon events inreal time as those events are assigned to the events pool. That is,event arrival rules identify alerts in dependence upon events beforeclosing the events pool. Such rules are flexible and may be tailored toa particular distributed computing system and its functions.

An alert according to embodiments of the present invention is a refinedidentification of an occurrence, such as an error based upon more thanone event, and therefore provides an identification of the occurrence inthe context of its operation in the distributed processing system. Oftenan alert may be a notification of a particular error type of occurrencethat is identified in dependence upon the plurality of events receivedfrom one or more components of the data processing system, such as, forexample, a link failure among a plurality of devices each of which areproducing many events based upon the single link failure, or a powerfailure provoking thousands of events, and so on.

Alerts are often implemented as messages to be sent through a datacommunications network or shared memory. Typical alerts according toembodiments of the present invention have attributes attached to thembased upon the attributes of the events received from which they areidentified.

Events pool operation rules are configurable predetermined rules forcontrolling the operations of the events pool. Such rules includes rulesidentifying the initial predetermined period of time for each eventspool, rules dictating the length of time extended to the pool upon theassignment of each new event to the pool, rules dictating the minimumtime an event must be in a pool before that event is included in acollection of events when the pool is closed, rules governing theclosing of an events pool, and others as will occur to those of skill inthe art. Such rules are flexible and may be tailored to a particulardistributed computing system and its functions.

Event suppression rules are configurable predetermined rules forsuppressing one or more events in a closed pool of events used inidentifying alerts. That is, often events in the closed events pool maybe duplicate events, redundant events, or otherwise unnecessary orunhelpful events in identifying alerts. Such suppression rules aretypically predetermined to delete, drop, or otherwise ignore thosesuppressed events. Event suppression rules may for example dictate thatmore than a threshold number of events of a particular event type orcomponent type are to be suppressed. Such rules are also flexible andmay be tailored to a particular distributed computing system and itsfunctions.

Events pool closure rules are configurable predetermined rules foridentifying alerts in dependence upon unsuppressed events in the closedevents pool and alerts identified by the event arrival rules. That is,events pool closure rules identify new alerts in dependence upon one ormore or even all of the unsuppressed events in the closed events pool.The events pool closure rules also identify alerts in dependence uponthe alerts identified by the event arrival rules or a combination of thealerts identified by the event arrival rules and one or more of theunsuppressed events in the closed events pool.

The method of FIG. 6 also includes identifying (610) by the eventanalyzer in dependence upon the event arrival rules and the eventsassigned to the events pool one or more alerts (314). Identifying (610)by the event analyzer in dependence upon the event arrival rules and theevents assigned to the events pool one or more alerts (314) may becarried out by identifying alerts in dependence upon one or moreattributes of the events as that event is assigned to the events pool.Identifying (610) by the event analyzer in dependence upon the eventarrival rules and the events assigned to the events pool one or morealerts (314) may be carried by comparing the attributes of the events tothe event arrival rules and identifying as a result of the comparisonone or more alerts. Such attributes may include the type of componentfrom which the event was received, the type of component creating theevent, the identification of the component creating the event, the timethe event was created or received, an error reported in the event, andmany others as will occur to those of skill in the art.

The method of FIG. 6 also includes closing (612), by the event analyzerin dependence upon the events pool operation rules, the events pool(312). Closing (612), by the event analyzer in dependence upon theevents pool operation rules, the events pool (312) may be carried out bydetermining that conditions dictated by the events pool operation ruleshave been met to stop assigning new events to the events pool andidentifying in dependence upon those events pool operation rules theparticular events that are included in the closed pool of events.

Closing the events pool may be carried out by determining that theinitial period of time for the events pool and any particular periods oftime for events received in the events pool extended to the initialperiod of time have expired. In such cases, if no new events arereceived prior to the expiration of the initial period of time for theevents pool and any particular periods of time for events received inthe events pool extended to the initial period of time the pool isclosed.

Closing the events pool may also be carried out by determining that amaximum duration for the events pool has expired. In such cases,regardless of the number of new events being received after a maximumduration for the events pool has expired the pool is closed. In suchembodiments, a maximum duration for the events pool prevents the eventspool from including more events than are useful for relevant alertdelivery according to embodiments of the present invention.

The method of FIG. 6 also includes determining (614), by the eventsanalyzer in dependence upon the event suppression rules, whether tosuppress one or more events in the closed events pool (312). Determining(614), by the events analyzer in dependence upon the event suppressionrules, whether to suppress one or more events in the closed events pool(312) may be carried out by determining in dependence upon theattributes of one or more events in the closed pool whether to delete,drop, or otherwise ignore one or more of the events in the closed pool.

The method of FIG. 6 includes identifying (616) by the event analyzer independence upon the events pool closure rules and any unsuppressedevents assigned to the events pool, one or more additional alerts (617).Identifying (616) by the event analyzer in dependence upon the eventspool closure rules and any unsuppressed events assigned to the eventspool, one or more additional alerts (617) may be carried out byidentifying alerts in dependence upon one or more attributes of theevents as that event is assigned to the events pool. Identifying (616)by the event analyzer in dependence upon the events pool closure rulesand any unsuppressed events assigned to the events pool, one or moreadditional alerts (617) may be carried out by selecting the unsuppressedevents for the events pool, comparing the attributes of the unsuppressedevents of the events pool to the pool closure rules, and identifying asa result of the comparison one or more additional alerts. Suchattributes may include the type of component from which one or more ofthe unsuppressed events are received, the type of components creatingthe unsuppressed events, the identification of the component creatingthe unsuppressed events, the time the events were created or received,one or more errors reported by the events event, the number of events inthe pool, and many others as will occur to those of skill in the art.

The method of FIG. 6 includes sending (618) by the event analyzer to analert analyzer all the alerts identified by the event analyzer. Sending(618) by the event analyzer to an alert analyzer all the alerts (314)identified by the event analyzer may be carried out by sending a messagecontaining the alerts from the event analyzer to the alert analyzer.Such a message may be sent from the event analyzer to the alert analyzeracross a network, through shared memory, or in other ways as will occurto those of skill in the art.

The method of FIG. 6 includes assigning (620) by the alert analyzer theidentified alerts to an alerts pool (324). An alerts pool according tothe method of FIG. 6 has a predetermined initial period of time and inthe example of FIG. 6 assigning (620) by the alert analyzer theidentified alerts to an alerts pool (324) includes extending for eachalert assigned to the alerts pool the predetermined initial period oftime by a particular period of time assigned to the alert. Assigning(620) by the alert analyzer the identified alerts to an alerts pool(324) also may be carried out in dependence upon attributes of thealerts. Such attributes may include an identification or type of thecomponent upon which an occurrence occurred to create the event that wasused to identify the alert, the alert ID, the alert type, and so on aswill occur to those of skill in the art.

The method of FIG. 6 includes determining (622) by the alert analyzer independence upon alert analysis rules (322) and the alerts in the alertspool whether to suppress any alerts. Determining (622) by the alertanalyzer in dependence upon alert analysis rules (322) and the alerts inthe alerts pool whether to suppress any alerts may be carried out independence upon one or more attributes of the alerts. Such attributesmay include an identification or type of the component upon which anoccurrence occurred to create the event that was used to identify thealert, the alert ID, the alert type, and so on as will occur to those ofskill in the art. In such embodiments, determining (622) by the alertanalyzer in dependence upon alert analysis rules (322) and the alerts inthe alerts pool whether to suppress any alerts may be carried out bycomparing the attributes of the alerts in the alerts pool to the alertanalysis rules and identifying as a result of the comparison one or morealerts for suppression according to the event analysis rules.

The method of FIG. 6 includes delivering (628) the unsuppressed alertsto one or more components of the distributed processing system.Delivering (628) the unsuppressed alerts to one or more components ofthe distributed processing system may be carried out by sending amessage containing the alert to one or more components of thedistributed processing system. In many cases, an alert may be sent as amessage to a systems administrator advising the systems administrator ofone or more occurrences within the distributed processing system.

As mentioned above, alert analysis rules may select additional alerts orsuppress alerts in dependence upon events. In such embodiments,determining whether to suppress any alerts includes selecting events anddetermining whether to suppress any alerts in dependence upon theselected events. The method of FIG. 6 therefore also includesidentifying (626) by the alert analyzer in dependence upon alertanalysis rules (322), the alerts in the alerts pool (324), and anyselected events one or more additional alerts and in the method of FIG.6, delivering (628) the unsuppressed alerts also includes delivering(630) any additional alerts to one or more components of the distributedprocessing system.

For further explanation, FIG. 7 sets forth a flow chart illustrating anexemplary method of adaptive clock throttling for event processing in adistributed processing system according to embodiments of the presentinvention. The method of FIG. 7 includes an event processing system(700) receiving (702) a plurality (750) of events from one or morecomponents (701) of the distributed processing system. An eventprocessing system may include an event and alert analysis module, suchas the event and alert analysis module (124) of FIGS. 1-3. Receiving(702) a plurality (750) of events from one or more components (701) ofthe distributed processing system may be carried out by components ofthe distributed processing system transmitting events to a monitor ofthe event and alert analysis module of an event processing system; anevent and alert analysis module periodically polling or retrievingevents from the components of the distributed processing system; writingthe received or retrieved events into an event queue; and loading theevents from the event queue into an event analyzer.

The method of FIG. 7 also includes the event processing system (700)determining (704) that an arrival attribute (780) of the plurality (750)of events exceeds an arrival threshold (760). An arrival attribute is anindication of arrival of events at the event processing system. Examplesof arrival attributes include a general arrival rate at which eventsarrive at the event processing system, an event analyzer arrival rate atwhich events arrive at a particular event analyzer of the eventprocessing system, a component event arrival rate at which events arrivefrom a particular component of the distributed processing system, or anycombination thereof. Measurement for arrival may be based on any numberof instances, such as an occurred time or a logged time. An occurredtime may represent the time the event was generated as a result of theoccurrence that caused the event. A logged time may represent the timein which the event is included in the events queue. An arrival thresholdis a predetermined value that corresponds to a maximum arrivalattribute. For example, if the arrival attribute is a component eventarrival rate, then the arrival threshold may be a maximum componentevent arrival rate. As another example, if the arrival attribute is anevent analyzer arrival rate, then the arrival threshold may be a maximumevent analyzer arrival rate. In these examples, exceeding either themaximum component event arrival rate or the maximum event analyzerarrival rate threshold may correspond to a rate indicative of aparticular type of high event arrival situation, such as an event storm.

An events storm, as that term is used here, is the result of anoccurrence in the distributed processing system that causes anoverwhelming number of events to be reported by components of thedistributed processing system. Such occurrences that may cause an eventsstorm may include the loss of an entire circuit providing power to manycomponents of the data processing system, catastrophic failure of anumber of components of the distributed processing system and others aswill occur to those of skill in the art. Events storms are often calledReliability, Availability, and Serviceability (RAS) storm. According toembodiments of the present invention, determining (704) that an arrivalattribute (780) of the plurality (750) of events exceeds an arrivalthreshold (760) may serve as an indication of an event storm.Determining (704) that an arrival attribute (780) of the plurality (750)of events exceeds an arrival threshold (760) may be carried out bycounting the number of received events over a predetermined period oftime and comparing that ratio to the arrival threshold.

The method of FIG. 7 also includes the event processing system (700)adjusting (706), in response to determining that the arrival attribute(780) of the plurality (750) of events exceeds the arrival threshold(760), a clock speed (790) of at least one of the event processingsystem (700) and a component (701) of the distributed processing system.A clock speed may be an indication of an operating frequency of aprocessor belonging to either the event processing system or a componentof the distributed processing system. Adjusting (706) a clock speed(790) of at least one of the event processing system (700) and acomponent (701) of the distributed processing system may be carried outby raising or lowering a clock speed of one or more processors of one ormore components of the distributed processing system or the eventprocessing system. Raising or lowering a clock speed may be carried outby transmitting a message to a particular component of the distributedprocessing system; writing a higher or lower value to a register in asubcomponent component that controls the operating frequency of aparticular component; or any other method of throttling that is known toone of skill in the art.

For example, the event processing system may lower the clock speed of aparticular component producing events during an event storm. Reducingthe clock speed of the particular component may reduce the rate at whichthe particular component is producing events, thus reducing the rate andnumber of events that the event processing system receives during theevent storm from that particular component. Reducing the number ofevents that the event processing system receives may allow an eventstorm to subside and the event processing system to more effectivelyconsume and process the events.

As another example, the event processing system may increase the clockspeed of a particular component producing events during an event storm.Increasing the clock speed of the particular component may increase therate at which the particular component is producing events, thusincreasing the rate and number of events that the event processingsystem receives during the event storm from that particular component.Increasing the rate that events are received from a particular componentmay increase the number of important events received during an eventstorm, thus allowing the event processing system to more effectivelyconsume and process the events.

That is, according to embodiments of the present invention, the eventprocessing system, by adjusting the clock speed of a component, mayincrease or decrease the rate at which events are received from thecomponent. Whether the event processing system wants to increase ordecrease the arrival rate of events from a component may depend on avariety of factors, such as the type of events the component isproducing.

As another example, the event processing system may increase the clockspeed of one or more processors within the event processing system.Increasing the clock speed of the event processing system may increasethe rate at which the event processing system is analyzing andprocessing events, thus allowing the event processing system to moreeffectively consume and process the events.

For further explanation, FIG. 8 sets forth a flow chart illustrating anadditional method of adaptive clock throttling for event processing in adistributed processing system according to embodiments of the presentinvention. The method of FIG. 8 is similar to the method of FIG. 7 inthat the method of FIG. 8 also includes receiving (702) a plurality(750) of events from one or more components (701) of the distributedprocessing system; determining (704) that an arrival attribute (780) ofthe plurality (750) of events exceeds an arrival threshold (760); and inresponse to determining that the arrival attribute (780) of theplurality (750) of events exceeds the arrival threshold (760), adjusting(706) a clock speed (790) of at least one of the event processing system(700) and a component (701) of the distributed processing system.

In the method of FIG. 8, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system includes the event processing system (700)determining (802) for each component a total number (850) of eventsreceived from the component. Determining (802) for each component atotal number (850) of events received from the component may be carriedout by counting the number of events received from a component during aparticular time period.

In the method of FIG. 8, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system also includes the event processing system(700) identifying (804) any components (891) of the distributedprocessing system having a total number of events that exceed apredetermined total event number threshold (871). Identifying (804) anycomponents (891) of the distributed processing system having a totalnumber of events that exceed a predetermined total event numberthreshold (871) may be carried out by examining the data associated withthe event to retrieve a component identification (870) indicating thecomponent that produced the event; and storing the componentidentifications (870) of the identified components (891).

In the method of FIG. 8, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system also includes the event processing system(700), for each of the identified components (891), reducing the clockspeed of one or more processors (899) of the identified component (891).Reducing the clock speed of one or more processors (899) of theidentified component (891) may be carried out by transmitting a messageto a particular component of the distributed processing system; writinga higher or lower value to a register in a subcomponent component thatcontrols the operating frequency of a particular component; or any othermethod of throttling that is known to one of skill in the art.

For example, during an event storm, the event processing system mayidentify components producing a large number of events and send aninstruction to reduce the clock speed of the identified components.Reducing the clock speed of the identified components may reduce therate at which the identified components are producing events, thusreducing the rate and number of events that the event processing systemreceives during the event storm. Reducing the number of events that theevent processing system receives may allow an event storm to subside andthe event processing system to more effectively consume and process theevents.

For further explanation, FIG. 9 sets forth a flow chart illustrating anadditional method of adaptive clock throttling for event processing in adistributed processing system according to embodiments of the presentinvention. The method of FIG. 9 is similar to the method of FIG. 7 inthat the method of FIG. 9 also includes receiving (702) a plurality(750) of events from one or more components (701) of the distributedprocessing system; determining (704) that an arrival attribute (780) ofthe plurality (750) of events exceeds an arrival threshold (760); and inresponse to determining that the arrival attribute (780) of theplurality (750) of events exceeds the arrival threshold (760), adjusting(706) a clock speed (790) of at least one of the event processing system(700) and a component (701) of the distributed processing system.

In the method of FIG. 9, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system includes the event processing system (700)identifying (902) within the plurality (750) of events, events (950) ofone or more particular predetermined types (952). A predetermined typemay be any indication of any type of event classification, such as eventidentification number, event type, location information, or any otherevent indication information. Identifying (902) within the plurality(750) of events, events (950) of one or more particular predeterminedtypes (952) may be carried out by: for each event, examining dataassociated with event to determine if the event has some attributematching one of the predetermined types, such as a matching location,type, or identification number. For example, the predetermined types mayindicate type of events that the event processing system places a higherpriority on during an event storm. As another example, the predeterminedtypes may indicate types of events that the event processing systemplaces a lower priority on during an event storm. In a particularembodiment, the predetermined types may include both types of the eventsthat the event processing system places a higher priority on during anevent storm and types of the events that the event processing systemplaces a lower priority on during an event storm. In this example, theevent processing system can take into consideration the type of theevent in adjusting the clock speed of the identified component.

In the method of FIG. 9, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system also includes the event processing system(700) identifying (904) the components (991) of the distributedprocessing system that produced the identified events (950). Identifying(904) the components (991) of the distributed processing system thatproduced the identified events (950) may be carried out by examining thedata associated with the event to retrieve a component identification(970) indicating the component that produced the event; and storing thecomponent identifications (970) of the identified components (991).

In the method of FIG. 9, adjusting (706) a clock speed (790) of at leastone of the event processing system (700) and a component (701) of thedistributed processing system also includes the event processing system(700), for each of the identified components (991), adjusting (906)based on the particular predetermined type of the events produced by thecomponent, the clock speed (990) of one or more processors (999) of theidentified component (991). Adjusting (906) based on the particularpredetermined type of the events produced by the component, the clockspeed (990) of one or more processors (999) of the identified component(991) may be carried out by raising or lowering a clock speed of one orthe processors; transmitting a message to a particular component of thedistributed processing system; writing a higher or lower value to aregister in a subcomponent component that controls the operatingfrequency of a particular component; or any other method of throttlingthat is known to one of skill in the art.

For example, the event processing system may classify an informationaltype event as a predetermined event type that is a lower priority duringan event storm. In this example, during an event storm, the eventprocessing system may identify components producing a large number ofinformational events and send an instruction to reduce the clock speedof the identified components. Reducing the clock speed of the identifiedcomponents may reduce the rate at which the identified components areproducing events, thus reducing the rate and number of information typeevents that the event processing system receives during the event storm.Reducing the number of events that the event processing system receivesmay allow an event storm to subside and the event processing system tomore effectively consume and process the events.

As another example, the event processing system may classify a powertype event as a predetermined event type that is a higher priorityduring an event storm. In this example, during an event storm, the eventprocessing system may identify components producing power events andsend an instruction to increase the clock speed of the identifiedcomponents. Increasing the clock speed of the identified components mayincrease the rate at which the identified components are producingevents, thus increasing the rate of events that the event processingsystem receives during the event storm from the identified components.Increasing the rate that events are received from a particular componentmay increase the number of important events received during an eventstorm, thus allowing the event processing system to more effectivelyconsume and process the events.

For further explanation, FIG. 10 sets forth a flow chart illustrating anadditional method of adaptive clock throttling for event processing in adistributed processing system according to embodiments of the presentinvention. The method of FIG. 10 is similar to the method of FIG. 7 inthat the method of FIG. 10 also includes receiving (702) a plurality(750) of events from one or more components (701) of the distributedprocessing system; determining (704) that an arrival attribute (780) ofthe plurality (750) of events exceeds an arrival threshold (760); inresponse to determining that the arrival attribute (780) of theplurality (750) of events exceeds the arrival threshold (760), adjusting(706) a clock speed (790) of at least one of the event processing system(700) and a component (701) of the distributed processing system.

The method of FIG. 10 also includes the event processing system (700)adjusting (1002), in response to determining that the arrival attribute(780) of the plurality of events (750) exceeds the arrival threshold(760), an event retrieval time period (1050) for one or more components(701) of the distributed processing system. An event retrieval period isthe amount of time between retrieval of events from a component of thedistributed processing system and the event processing system.Increasing the event retrieval time period reduces the retrieval rate orrate at which events are pulled from a component. Reducing the rate atwhich events are received from a component reduces the rate and numberof events that the event processing system receives during the eventstorm. Reducing the number of events that the event processing systemreceives may allow an event storm to subside and the event processingsystem to more effectively consume and process the events. Conversely,decreasing the event retrieval time period increases the retrieval rate.Increasing the rate that events are retrieved from a particularcomponent may increase the number of important events received during anevent storm, thus allowing the event processing system to moreeffectively consume and process the events. Adjusting (1002) an eventretrieval time period (1050) for one or more components (701) of thedistributed processing system may be carried out by changing one or morevalues in a register to indicate a change in a retrieval time period.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present invention may be written in any combination ofone or more programming languages, including an object orientedprogramming language such as Java, Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

It will be understood from the foregoing description that modificationsand changes may be made in various embodiments of the present inventionwithout departing from its true spirit. The descriptions in thisspecification are for purposes of illustration only and are not to beconstrued in a limiting sense. The scope of the present invention islimited only by the language of the following claims.

What is claimed is:
 1. A method of adaptive clock throttling for event processing in a distributed processing system, the method comprising: receiving, by an event processing system, a plurality of events from one or more components of the distributed processing system; determining, by the event processing system, that an arrival attribute of the plurality of events exceeds an arrival threshold; and in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system, said adjusting including: determining for each component, by the event processing system, a total number of events received from the component; identifying, by the event processing system, any components of the distributed processing system having a total number of events that exceed a predetermined total event number threshold; and for each of the identified components, reducing, by the event processing system, the clock speed of one or more processors of the identified component.
 2. The method of claim 1 wherein adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system includes: identifying within the plurality of events, by the event processing system, events of one or more particular predetermined types; identifying, by the event processing system, the components of the distributed processing system that produced the identified events; and for each of the identified components, adjusting based on the particular predetermined type of the events produced by the component, by the event processing system, the clock speed of one or more processors of the identified component.
 3. The method of claim 1 further comprising in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, an event retrieval time period for one or more components of the distributed processing system.
 4. The method of claim 1 wherein the arrival attribute is a component event arrival rate; and wherein the arrival threshold is a maximum component event arrival rate threshold.
 5. The method of claim 1 wherein the arrival attribute is an event analyzer arrival rate; and wherein the arrival threshold is a maximum event analyzer arrival rate threshold.
 6. An apparatus for adaptive clock throttling for event processing in a distributed processing system, the apparatus comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that when executed by the computer processor cause the apparatus to carry out the steps of: receiving, by an event processing system, a plurality of events from one or more components of the distributed processing system; determining, by the event processing system, that an arrival attribute of the plurality of events exceeds an arrival threshold; and in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system, said adjusting including: identifying within the plurality of events, by the event processing system, events of one or more particular predetermined types; identifying, by the event processing system, the components of the distributed processing system that produced the identified events; and for each of the identified components, adjusting based on the particular predetermined type of the events produced by the component, by the event processing system, the clock speed of one or more processors of the identified component.
 7. The apparatus of claim 6 wherein adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system includes: determining for each component, by the event processing system, a total number of events received from the component; identifying, by the event processing system, any components of the distributed processing system having a total number of events that exceed a predetermined total event number threshold; and for each of the identified components, reducing, by the event processing system, the clock speed of one or more processors of the identified component.
 8. The apparatus of claim 6 further comprising computer program instructions that when executed by the computer processor cause the apparatus to carry out the steps of in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, an event retrieval time period for one or more components of the distributed processing system.
 9. The apparatus of claim 6 wherein the arrival attribute is a component event arrival rate; and wherein the arrival threshold is a maximum component event arrival rate threshold.
 10. The apparatus of claim 6 wherein the arrival attribute is an event analyzer arrival rate; and wherein the arrival threshold is a maximum event analyzer arrival rate threshold.
 11. A computer program product for adaptive clock throttling for event processing in a distributed processing system, the computer program product disposed upon a non-transitory computer readable storage medium, the computer program product comprising computer program instructions that when executed by a computer cause the computer to carry out the steps of: receiving, by an event processing system, a plurality of events from one or more components of the distributed processing system; determining, by the event processing system, that an arrival attribute of the plurality of events exceeds an arrival threshold; and in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system, including: determining for each component, by the event processing system, a total number of events received from the component; identifying, by the event processing system, any components of the distributed processing system having a total number of events that exceed a predetermined total event number threshold; and for each of the identified components, reducing, by the event processing system, the clock speed of one or more processors of the identified component.
 12. The computer program product of claim 11 wherein adjusting, by the event processing system, a clock speed of at least one of the event processing system and a component of the distributed processing system includes: identifying within the plurality of events, by the event processing system, events of one or more particular predetermined types; identifying, by the event processing system, the components of the distributed processing system that produced the identified events; and for each of the identified components, adjusting based on the particular predetermined type of the events produced by the component, by the event processing system, the clock speed of one or more processors of the identified component.
 13. The computer program product of claim 11 further comprising computer program instructions that when executed by a computer cause the computer to carry out the steps of in response to determining that the arrival attribute of the plurality of events exceeds the arrival threshold, adjusting, by the event processing system, an event retrieval time period for one or more components of the distributed processing system.
 14. The computer program product of claim 11 wherein the arrival attribute is a component event arrival rate; and wherein the arrival threshold is a maximum component event arrival rate threshold.
 15. The computer program product of claim 11 wherein the arrival attribute is an event analyzer arrival rate; and wherein the arrival threshold is a maximum event analyzer arrival rate threshold. 